**NotImplementedError** : Cannot convert RV to a tensor variable inside pm.deterministic()

Questions v5
1

[reposted from frequently asked as I am not sure if that was the right place to ask]

Hi, i’m following the Statistical Rethinking textbook with the PYMC code examples here.

I followed the example and used aesara’s shared to manipulate a predictor variable but was met with the following error during pm.Model() on the pm.Deterministic line 7:

----> 7 mu = pm.Deterministic(‘mu’, a + ba * age_shared + bm * marriage_shared)
NotImplementedError : Cannot convert ba to a tensor variable.

Code:

marriage_shared = shared(data["Marriage_std"].values)
age_shared = shared(data["MedianAgeMarriage_std"].values)

with pm.Model() as m5_3a:
      # A -> D <- M
      sigma = pm.Exponential('sigma', 1)
      a = pm.Normal('a', 0, 0.2)
      ba = pm.Normal('ba', 0, 0.5)
      bm = pm.Normal('bm', 0, 0.5)
      mu = pm.Deterministic('mu', a + ba * age_shared + bm * marriage_shared)
      divorce = pm.Normal('divorce', mu, sigma, observed= d['divorce_std'])
     # A -> M
      sigma_m = pm.Exponential('sigma_m', 1)
      am = pm.Normal('am', 0, 0.2)
      bam = pm.Normal('bam', 0 , 0.5)
      mu_m = pm.Deterministic('mu_m', am + bam * age_shared)
      marriage = pm.Normal('marriage', mu_m, sigma_m, observed= d['marriage_std'])
  
      trace5_3a = pm.sample()

Versions:
pymc = 5.0.1
aesara = 2.8.10

Any idea what went wrong?

2

PyMC 5 requires PyTensor, not Aesara. You should therefore use pytensor.shared instead of aesara.shared

1 Like
3

Hey newbie here. Perhaps make this step more explicit in a place where newbies can definitely get to. Was browsing through your docs about using shared variables, ended up looking at v3 docs calling theano.shared; then got to some random place (not on your official websites) and ended up looking at people calling aesara.shared. Now finally…

4

Yeah that’s definitely suboptimal. Our official docs are versioned now so you can always check the version on the bottom right. The official notebook examples have a footer that indicates what version it was ran on.

Google is sometimes too slow to update search results and discourse issues can also become stale :confused: